Amir Toliyat is an Assistant Professor of Information Systems & Informatics in the Department of Marketing at the Lucille and Jay Chazanoff School of Business, College of Staten Island, CUNY. He earned a Ph.D. in Computer Science from the CUNY Graduate Center. His research explores artificial intelligence and information systems for responsible, data-driven decision-making, with interests in natural language processing and large language models, responsible AI, business analytics, cybersecurity and risk, anomaly detection, computer vision, and decision-support systems. His applied work spans business, aviation and transportation, healthcare, and digital services. Before joining CSI, he served as a tenure-track Assistant Professor of Computer Science at Vaughn College and taught at several CUNY colleges as an adjunct assistant professor. His teaching emphasizes hands-on projects, clear interpretation of analytical results, and connecting technical concepts to practical organizational problems.
Degrees
Ph.D. in Computer Science, CUNY Graduate Center
M.Phil., CUNY Graduate Center
M.S., IAUM
B.S., Sadjad University
Selected publications and recognition:
- Gorman, C., Toliyat, A., Vatankhah, M., & Fuller, C. (2026). A Protocol-Aware AI Framework for Securing CPDLC Communications. ICNS 2026 - 2nd Place Best Student Paper.
- Vatankhah, M., & Toliyat, A. (2025). Deep Learning in Healthcare: Unsupervised Anomaly Detection with Enhanced Scoring Method. ICBRA 2025, 71-76.
- Toliyat, A., Filatova, E., & Etemadpour, R. (2025). Inter- Annotator Agreement and Its Reflection in LLMs and Responsible AI. FLAIRS 2025.
- Toliyat, A., Levitan, S. I., Peng, Z., & Etemadpour, R. (2022). Asian hate speech detection on Twitter during COVID-19. Frontiers in Artificial Intelligence, 5.
- Chun, A., Li, A., Toliyat, A., Geller, J. (2020). Tracking Citizen’s Concerns during COVID-19 Pandemic. In Proceedings of the 21st Annual International Conference on Digital Government Research (dg.o '20). Association for Computing Machinery, New York, NY, USA, 322–323.
Research Interests
Research interests include AI-enabled information systems; NLP and large language models; responsible and explainable AI; business and data analytics; cybersecurity and risk management; anomaly detection; computer vision; and decision support. Current work examines trustworthy AI for structured and safety-critical communications, including aviation cybersecurity, and the use of analytics to support organizational decision-making.
Teaching
Student-centered, applied teaching that integrates information systems, programming, databases, data analytics, artificial intelligence and machine learning, cybersecurity, and decision support. Courses use hands-on projects and real scenarios to help students translate data and models into defensible business and operational decisions.
Currently BUS-215
Courses and Areas of Expertise
Information Management; Business Analytics; Data Science and Machine Learning; Database Fundamentals; Python and C++ Programming; Data Structures and Algorithms; Computer Networks; Cybersecurity; and AI Applications.
Student Mentoring and Recognition
Mentored student research in aviation cybersecurity; a coauthored student paper on securing CPDLC communications received 2nd Place Best Student Paper at ICNS 2026.
Contact Information
Monday 9 am to 2 pm